A Bayesian method for addressing multinomial misclassification with applications for alcohol epidemiological modeling

William J. Parish (), Arnie Aldridge () and Martijn van Hasselt
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William J. Parish: RTI International
Arnie Aldridge: RTI International

Stata Journal, 2024, vol. 24, issue 1, 113-137

Abstract: In this article, we describe a new command, bamm, that implements a Bayesian method for addressing misclassification in multinomial data; see Swartz et al. (2004, Canadian Journal of Statistics 32: 285–302). We also describe a postestimation command, bammdx, that was developed to provide additional esti- mation diagnostics. We describe the method and the new commands and then present results from both a simulation study demonstrating bamm’s performance under a known misclassification data-generating process and an empirical example from alcohol epidemiology modeling.

Keywords: bamm; bammdx; Bayesian; multinomial; misclassification; alcohol; liver cirrhosis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1177/1536867X241233671

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